Health care workers who were at high risk of contracting SARS appear not only to have chronic stress but also higher levels of depression and anxiety. Front-line staff could benefit from stress management as part of preparation for future outbreaks.
S evere acute respiratory syndrome (SARS) is caused by a novel coronavirus (1) and has placed extraordinary demands upon health care systems worldwide. Unlike previous public health challenges, health care workers (HCWs) comprised a high proportion of the nearly 8000 infected persons across 29 countries: the percentage of infected HCWs ranged from 3% in the US, where most cases originated from international air travel (2), to as high as 22% in Hong Kong (3), 33% in Taiwan (4), and 51% in Toronto (5), with a mortality rate of 15% (6). Since early SARS resembles influenza (7), widespread avoidance of crowded places occurred in Hong Kong. HCWs were rapidly deployed to SARS wards. A qualitative study of 11
Autism is a disorder of neurodevelopment resulting in pervasive abnormalities in social interaction and communication, repetitive behaviours and restricted interests. There is evidence for functional abnormalities and metabolic dysconnectivity in 'social brain' circuitry in this condition, but its structural basis has proved difficult to establish reliably. Explanations for this include replication difficulties inherent in 'region of interest' approaches usually adopted, and variable inclusion criteria for subjects across the autism spectrum. Moreover, despite a consensus that autism probably affects widely distributed brain regions, the issue of anatomical connectivity has received little attention. Therefore, we planned a fully automated voxel-based whole brain volumetric analysis in children with autism and normal IQ. We predicted that brain structural changes would be similar to those previously shown in adults with autism spectrum disorder and that a correlation analysis would suggest structural dysconnectivity. We included 17 stringently diagnosed children with autism and 17 age-matched controls. All children had IQ >80. Using Brain Activation and Morphological Mapping (BAMM) software, we measured global brain and tissue class volumes and mapped regional grey and white matter differences across the whole brain. With the expectation that volumes of interconnected regions correlate positively, we carried out a preliminary exploration of 'connectivity' in autism by comparing the nature of inter-regional grey matter volume correlations with control. Children with autism had a significant reduction in total grey matter volume and significant increase in CSF volume. They had significant localized grey matter reductions within fronto-striatal and parietal networks similar to findings in our previous study, and additional decreases in ventral and superior temporal grey matter. White matter was reduced in the cerebellum, left internal capsule and fornices. Correlation analysis revealed significantly more numerous and more positive grey matter volumetric correlations in controls compared with children with autism. Thus, using similar diagnostic criteria and image analysis methods in otherwise healthy populations with an autistic spectrum disorder from different countries, cultures and age groups, we report a number of consistent findings. Taken together, our data suggest abnormalities in the anatomy and connectivity of limbic-striatal 'social' brain systems which may contribute to the brain metabolic differences and behavioural phenotype in autism.
Widespread structural dysconnectivity, including the subcortical region, is already present in neuroleptic-naive patients in their first episode of illness.
Shared genetic and environmental risk factors have been identified for autistic spectrum disorders (ASD) and schizophrenia. Social interaction, communication, emotion processing, sensorimotor gating and executive function are disrupted in both, stimulating debate about whether these are related conditions. Brain imaging studies constitute an informative and expanding resource to determine whether brain structural phenotype of these disorders is distinct or overlapping. We aimed to synthesize existing datasets characterizing ASD and schizophrenia within a common framework, to quantify their structural similarities. In a novel modification of Anatomical Likelihood Estimation (ALE), 313 foci were extracted from 25 voxel-based studies comprising 660 participants (308 ASD, 352 first-episode schizophrenia) and 801 controls. The results revealed that, compared to controls, lower grey matter volumes within limbic-striato-thalamic circuitry were common to ASD and schizophrenia. Unique features of each disorder included lower grey matter volume in amygdala, caudate, frontal and medial gyrus for schizophrenia and putamen for autism. Thus, in terms of brain volumetrics, ASD and schizophrenia have a clear degree of overlap that may reflect shared etiological mechanisms. However, the distinctive neuroanatomy also mapped in each condition raises the question about how this is arrived in the context of common etiological pressures.
Our study suggests that the underlying neurobiology in HFA and Asperger's syndrome is at least partly discrete. Future studies should therefore consider the history of language acquisition as a valuable tool to refine investigation of aetiological factors and management options in pervasive developmental disorders.
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